Changeset 16500 for branches/2974_Constants_Optimization/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters

Timestamp:

01/04/19 17:37:13 (6 years ago)

Author:

mkommend

Message:

#2974: Added intermediate version of new constants optimization for profiling.

Location:

branches/2974_Constants_Optimization

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/TreeToAutoDiffTermConverter.cs (modified) (2 diffs)

branches/2974_Constants_Optimization

@@ -1 +1 @@
 packages
+TestResults

@@ -1 +1 @@
 packages
+TestResults

branches/2974_Constants_Optimization/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/TreeToAutoDiffTermConverter.cs

@@ -131 +131 @@
     }
 
-    public static bool TryConvertToAutoDiff(ISymbolicExpressionTree tree, bool makeVariableWeightsVariable, bool addLinearScalingTerms, Dictionary<DataForVariable, AutoDiff.Variable> parameters,
-      out ParametricFunction func,
-      out ParametricFunctionGradient func_grad,
-      out double[] initialConstants
-  ) {
+    public static bool TryConvertToAutoDiff(ISymbolicExpressionTree tree, bool addLinearScalingTerms, IEnumerable<DataForVariable> variables,
+      out IParametricCompiledTerm autoDiffTerm, out double[] initialConstants) {
       // use a transformator object which holds the state (variable list, parameter list, ...) for recursive transformation of the tree
-      var transformator = new TreeToAutoDiffTermConverter(makeVariableWeightsVariable, parameters);
+      //TODO change ctor
+      var transformator = new TreeToAutoDiffTermConverter(true);
+      var parameters = new AutoDiff.Variable[variables.Count()];
+
+      int i = 0;
+      foreach(var variable in variables) { 
+        var autoDiffVar = new AutoDiff.Variable();
+        transformator.parameters.Add(variable, autoDiffVar);
+        parameters[i] = autoDiffVar;
+        i++;
+      }
+
       AutoDiff.Term term;
       try {
-
-
+        term = transformator.ConvertToAutoDiff(tree.Root.GetSubtree(0));
         if (addLinearScalingTerms) {
-          // scaling variables α, β are given at the beginning of the parameter vector
+          // scaling variables α, β are given at the end of the parameter vector
           var alpha = new AutoDiff.Variable();
           var beta = new AutoDiff.Variable();
+
+          term = term * alpha + beta;
+
+          transformator.variables.Add(alpha);
           transformator.variables.Add(beta);
-          transformator.variables.Add(alpha);
-          term = transformator.ConvertToAutoDiff(tree.Root.GetSubtree(0));
-          term = term * alpha + beta;
-        } else {
-          term = transformator.ConvertToAutoDiff(tree.Root.GetSubtree(0));
-        }
-
-        var compiledTerm = term.Compile(transformator.variables.ToArray(), parameters.Values.ToArray());
-        func = (vars, @params) => compiledTerm.Evaluate(vars, @params);
-        func_grad = (vars, @params) => compiledTerm.Differentiate(vars, @params);
+
+          transformator.initialConstants.Add(1.0);
+          transformator.initialConstants.Add(0.0);
+        }
+
+        var compiledTerm = term.Compile(transformator.variables.ToArray(), parameters);
+        autoDiffTerm = compiledTerm;
         initialConstants = transformator.initialConstants.ToArray();
 
         return true;
       } catch (ConversionException) {
-        func = null;
-        func_grad = null;
+        autoDiffTerm = null;
         initialConstants = null;
       }
@@ -174 +181 @@
     private readonly bool makeVariableWeightsVariable;
 
-    private TreeToAutoDiffTermConverter(bool makeVariableWeightsVariable, Dictionary<DataForVariable, AutoDiff.Variable> parameters = null) {
+    private TreeToAutoDiffTermConverter(bool makeVariableWeightsVariable) {
       this.makeVariableWeightsVariable = makeVariableWeightsVariable;
       this.initialConstants = new List<double>();
-      if (parameters == null)
-        this.parameters = new Dictionary<DataForVariable, AutoDiff.Variable>();
-      else
-        this.parameters = parameters;
+      this.parameters = new Dictionary<DataForVariable, AutoDiff.Variable>();
       this.variables = new List<AutoDiff.Variable>();
     }

@@ -1 +1 @@
 packages
+TestResults